---
license: apache-2.0
tags:
- nlp
- chatbot
- huggingface
datasets:
- dataset_name
metrics:
- accuracy
model_creator: Al Rafi
model_type: machine-learning
language: 
- en
- bn
finetuned_from: gpt-3.5
pipeline_tag: text-generation
---

# Model Card for RafiX

This modelcard aims to provide a detailed overview of the RafiX model, developed by Al Rafi. This model is designed to assist in various machine learning and AI tasks, particularly those related to coding, development, and other related areas.

## Model Details

### Model Description

RafiX is a machine learning model created by Al Rafi, developed with the aim of simplifying complex coding tasks, providing recommendations, and offering support in AI-related activities. The model is designed to work across a variety of applications, ranging from coding assistance to other development-related tasks.

- **Developed by:** Al Rafi (Made by coding & others)
- **Funded by:** Al Rafi
- **Shared by:** Al Rafi
- **Model type:** Machine Learning
- **Language(s) (NLP):** English, Bengali
- **License:** Apache-2.0
- **Finetuned from model:** GPT-3.5

### Model Sources

- **Repository:** [Hugging Face Repository](https://huggingface.co/alrafi/chatbot)
- **Demo:** [Model Demo](https://huggingface.co/alrafi/chatbot)

## Uses

### Direct Use

The RafiX model is intended to assist users in coding, machine learning tasks, and AI-related inquiries. It can be directly used to automate repetitive tasks, assist in coding, or provide recommendations for better practices in AI.

### Downstream Use

RafiX can be fine-tuned and integrated into larger applications, such as coding assistants, AI-based applications, or platforms requiring automation and machine learning assistance.

### Out-of-Scope Use

This model is not intended for malicious activities, and it may not perform well in tasks outside its designed scope, such as generating offensive content or handling sensitive data without proper safeguards.

## Bias, Risks, and Limitations

This model may exhibit biases depending on the data it was trained on, especially in terms of language and cultural contexts. It may also have limitations when dealing with tasks that require human-like judgment or creativity beyond its training data.

### Recommendations

Users should be aware of the model’s potential biases and limitations. It is recommended to validate the model’s outputs in critical applications, especially in areas where precision is crucial.

## How to Get Started with the Model

To get started with RafiX, use the following code snippet:

```python
import rafix

model = rafix.load_model("rafix")
result = model.generate("Your coding task here")
print(result)